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Shurui Gui
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2020 – today
- 2024
- [j3]Shurui Gui
, Hao Yuan
FlowX: Towards Explainable Graph Neural Networks via Message Flows. IEEE Trans. Pattern Anal. Mach. Intell. 46(7): 4567-4578 (2024) - [c6]Shurui Gui, Xiner Li, Shuiwang Ji:
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm. ICLR 2024 - [c5]Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji:
Graph Structure Extrapolation for Out-of-Distribution Generalization. ICML 2024 - [c4]Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji:
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency. ICML 2024 - [i10]Shurui Gui, Xiner Li, Shuiwang Ji:
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm. CoRR abs/2404.05094 (2024) - [i9]Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji:
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency. CoRR abs/2406.07598 (2024) - [i8]Xiner Li, Limei Wang, Youzhi Luo, Carl Edwards, Shurui Gui, Yuchao Lin, Heng Ji, Shuiwang Ji:
Geometry Informed Tokenization of Molecules for Language Model Generation. CoRR abs/2408.10120 (2024) - 2023
- [j2]Hao Yuan
Explainability in Graph Neural Networks: A Taxonomic Survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5782-5799 (2023) - [c3]Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji:
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization. NeurIPS 2023 - [i7]Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji:
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization. CoRR abs/2306.01103 (2023) - [i6]Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji:
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization. CoRR abs/2306.08076 (2023) - [i5]Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - 2022
- [c2]Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji:
GOOD: A Graph Out-of-Distribution Benchmark. NeurIPS 2022 - [i4]Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji:
GOOD: A Graph Out-of-Distribution Benchmark. CoRR abs/2206.08452 (2022) - [i3]Shurui Gui, Hao Yuan, Jie Wang, Qicheng Lao
FlowX: Towards Explainable Graph Neural Networks via Message Flows. CoRR abs/2206.12987 (2022) - 2021
- [j1]Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu
DIG: A Turnkey Library for Diving into Graph Deep Learning Research. J. Mach. Learn. Res. 22: 240:1-240:9 (2021) - [i2]Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan
DIG: A Turnkey Library for Diving into Graph Deep Learning Research. CoRR abs/2103.12608 (2021) - 2020
- [c1]Shurui Gui, Chaoyue Wang, Qihua Chen, Dacheng Tao:
FeatureFlow: Robust Video Interpolation via Structure-to-Texture Generation. CVPR 2020: 14001-14010 - [i1]Hao Yuan, Haiyang Yu, Shurui Gui, Shuiwang Ji:
Explainability in Graph Neural Networks: A Taxonomic Survey. CoRR abs/2012.15445 (2020)
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